balance Profiling Report

Dataset statistics

Number of variables	11
Number of observations	380
Missing cells	3
Missing cells (%)	0.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	32.8 KiB
Average record size in memory	88.3 B

Variable types

Numeric	8
Categorical	3

Alerts

`City` has a high cardinality: 366 distinct values	High cardinality
`Male Population` is highly correlated with `Female Population` and 3 other fields	High correlation
`Female Population` is highly correlated with `Male Population` and 3 other fields	High correlation
`Total Population` is highly correlated with `Male Population` and 3 other fields	High correlation
`Number of Veterans` is highly correlated with `Male Population` and 2 other fields	High correlation
`Foreign-born` is highly correlated with `Male Population` and 2 other fields	High correlation
`Male Population` is highly correlated with `Female Population` and 3 other fields	High correlation
`Female Population` is highly correlated with `Male Population` and 3 other fields	High correlation
`Total Population` is highly correlated with `Male Population` and 3 other fields	High correlation
`Number of Veterans` is highly correlated with `Male Population` and 3 other fields	High correlation
`Foreign-born` is highly correlated with `Male Population` and 3 other fields	High correlation
`Male Population` is highly correlated with `Female Population` and 2 other fields	High correlation
`Female Population` is highly correlated with `Male Population` and 2 other fields	High correlation
`Total Population` is highly correlated with `Male Population` and 2 other fields	High correlation
`Number of Veterans` is highly correlated with `Male Population` and 2 other fields	High correlation
`State Code` is highly correlated with `State`	High correlation
`State` is highly correlated with `State Code`	High correlation
`State` is highly correlated with `State Code`	High correlation
`Male Population` is highly correlated with `Female Population` and 3 other fields	High correlation
`Female Population` is highly correlated with `Male Population` and 3 other fields	High correlation
`Total Population` is highly correlated with `Male Population` and 3 other fields	High correlation
`Number of Veterans` is highly correlated with `Male Population` and 3 other fields	High correlation
`Foreign-born` is highly correlated with `Male Population` and 3 other fields	High correlation
`State Code` is highly correlated with `State`	High correlation
`City` is uniformly distributed	Uniform
`Unnamed: 0` has unique values	Unique
`Total Population` has unique values	Unique

Reproduction

Analysis started	2022-11-06 14:36:39.756121
Analysis finished	2022-11-06 14:37:14.262884
Duration	34.51 seconds
Software version	pandas-profiling v3.2.0
Download configuration	config.json

Unnamed: 0
Real number (ℝ_≥0)

UNIQUE

Distinct	380
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	495.3552632

Minimum	1
Maximum	1963
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	1
5-th percentile	31.9
Q1	162.75
median	381.5
Q3	742.5
95-th percentile	1400.7
Maximum	1963
Range	1962
Interquartile range (IQR)	579.75

Descriptive statistics

Standard deviation	416.141451
Coefficient of variation (CV)	0.8400868668
Kurtosis	0.8414430476
Mean	495.3552632
Median Absolute Deviation (MAD)	257.5
Skewness	1.120269433
Sum	188235
Variance	173173.7072
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1	0.3%
609	1	0.3%
639	1	0.3%
638	1	0.3%
634	1	0.3%
631	1	0.3%
625	1	0.3%
624	1	0.3%
616	1	0.3%
615	1	0.3%
Other values (370)	370	97.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1	0.3%
3	1	0.3%
4	1	0.3%
5	1	0.3%
6	1	0.3%
7	1	0.3%
8	1	0.3%
9	1	0.3%
10	1	0.3%
12	1	0.3%

Value	Count	Frequency (%)
1963	1	0.3%
1931	1	0.3%
1774	1	0.3%
1762	1	0.3%
1657	1	0.3%
1651	1	0.3%
1645	1	0.3%
1609	1	0.3%
1604	1	0.3%
1581	1	0.3%

City
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	366
Distinct (%)	96.3%
Missing	0
Missing (%)	0.0%
Memory size	3.1 KiB

Bloomington	3
Peoria	2
Glendale	2
Pasadena	2
Union City	2
Other values (361)	369

Length

Max length	20
Median length	16
Mean length	9.023684211
Min length	2

Characters and Unicode

Total characters	3429
Distinct characters	53
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	353 ?
Unique (%)	92.9%

Sample

1st row	Peoria
2nd row	Hampton
3rd row	Lakewood
4th row	Mesa
5th row	Bryan

Common Values

Value	Count	Frequency (%)
Bloomington	3	0.8%
Peoria	2	0.5%
Glendale	2	0.5%
Pasadena	2	0.5%
Union City	2	0.5%
Concord	2	0.5%
Aurora	2	0.5%
Jacksonville	2	0.5%
Richmond	2	0.5%
Rochester	2	0.5%
Other values (356)	359	94.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
san	13	2.6%
beach	10	2.0%
city	8	1.6%
santa	7	1.4%
valley	6	1.2%
new	4	0.8%
fort	4	0.8%
saint	4	0.8%
hills	4	0.8%
el	3	0.6%
Other values (401)	441	87.5%

Most occurring characters

Value	Count	Frequency (%)
a	345	10.1%
e	299	8.7%
n	276	8.0%
o	260	7.6%
l	219	6.4%
i	214	6.2%
r	200	5.8%
t	160	4.7%
s	132	3.8%
	124	3.6%
Other values (43)	1200	35.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2792	81.4%
Uppercase Letter	508	14.8%
Space Separator	124	3.6%
Dash Punctuation	3	0.1%
Other Punctuation	2	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	345	12.4%
e	299	10.7%
n	276	9.9%
o	260	9.3%
l	219	7.8%
i	214	7.7%
r	200	7.2%
t	160	5.7%
s	132	4.7%
d	93	3.3%
Other values (16)	594	21.3%

Uppercase Letter

Value	Count	Frequency (%)
C	56	11.0%
S	52	10.2%
B	43	8.5%
P	39	7.7%
A	32	6.3%
R	30	5.9%
M	28	5.5%
L	28	5.5%
F	24	4.7%
G	21	4.1%
Other values (14)	155	30.5%

Space Separator

Value	Count	Frequency (%)
	124	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	3	100.0%

Other Punctuation

Value	Count	Frequency (%)
'	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3300	96.2%
Common	129	3.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	345	10.5%
e	299	9.1%
n	276	8.4%
o	260	7.9%
l	219	6.6%
i	214	6.5%
r	200	6.1%
t	160	4.8%
s	132	4.0%
d	93	2.8%
Other values (40)	1102	33.4%

Common

Value	Count	Frequency (%)
	124	96.1%
-	3	2.3%
'	2	1.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3429	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	345	10.1%
e	299	8.7%
n	276	8.0%
o	260	7.6%
l	219	6.4%
i	214	6.2%
r	200	5.8%
t	160	4.7%
s	132	3.8%
	124	3.6%
Other values (43)	1200	35.0%

State
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	17
Distinct (%)	4.5%
Missing	0
Missing (%)	0.0%
Memory size	3.1 KiB

California	114
Texas	48
Florida	41
Illinois	19
Michigan	15
Other values (12)	143

Length

Max length	14
Median length	13
Mean length	8.463157895
Min length	4

Characters and Unicode

Total characters	3216
Distinct characters	33
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Illinois
2nd row	Virginia
3rd row	Colorado
4th row	Arizona
5th row	Texas

Common Values

Value	Count	Frequency (%)
California	114	30.0%
Texas	48	12.6%
Florida	41	10.8%
Illinois	19	5.0%
Michigan	15	3.9%
Colorado	15	3.9%
Arizona	14	3.7%
Washington	14	3.7%
Virginia	13	3.4%
Massachusetts	13	3.4%
Other values (7)	74	19.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
california	114	27.5%
texas	48	11.6%
florida	41	9.9%
new	22	5.3%
illinois	19	4.6%
michigan	15	3.6%
colorado	15	3.6%
arizona	14	3.4%
washington	14	3.4%
massachusetts	13	3.1%
Other values (9)	99	23.9%

Most occurring characters

Value	Count	Frequency (%)
a	488	15.2%
i	446	13.9%
o	302	9.4%
n	265	8.2%
r	253	7.9%
l	230	7.2%
s	154	4.8%
C	141	4.4%
e	115	3.6%
f	114	3.5%
Other values (23)	708	22.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2768	86.1%
Uppercase Letter	414	12.9%
Space Separator	34	1.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	488	17.6%
i	446	16.1%
o	302	10.9%
n	265	9.6%
r	253	9.1%
l	230	8.3%
s	154	5.6%
e	115	4.2%
f	114	4.1%
d	76	2.7%
Other values (10)	325	11.7%

Uppercase Letter

Value	Count	Frequency (%)
C	141	34.1%
M	48	11.6%
T	48	11.6%
F	41	9.9%
N	34	8.2%
I	29	7.0%
W	14	3.4%
A	14	3.4%
V	13	3.1%
Y	11	2.7%
Other values (2)	21	5.1%

Space Separator

Value	Count	Frequency (%)
	34	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3182	98.9%
Common	34	1.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	488	15.3%
i	446	14.0%
o	302	9.5%
n	265	8.3%
r	253	8.0%
l	230	7.2%
s	154	4.8%
C	141	4.4%
e	115	3.6%
f	114	3.6%
Other values (22)	674	21.2%

Common

Value	Count	Frequency (%)
	34	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3216	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	488	15.2%
i	446	13.9%
o	302	9.4%
n	265	8.2%
r	253	7.9%
l	230	7.2%
s	154	4.8%
C	141	4.4%
e	115	3.6%
f	114	3.5%
Other values (23)	708	22.0%

Median Age
Real number (ℝ_≥0)

Distinct	157
Distinct (%)	41.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	35.81736842

Minimum	22.9
Maximum	70.5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	22.9
5-th percentile	28.7
Q1	32.8
median	35.4
Q3	38.5
95-th percentile	43.755
Maximum	70.5
Range	47.6
Interquartile range (IQR)	5.7

Descriptive statistics

Standard deviation	4.911454859
Coefficient of variation (CV)	0.1371249502
Kurtosis	6.015550911
Mean	35.81736842
Median Absolute Deviation (MAD)	2.7
Skewness	1.053303375
Sum	13610.6
Variance	24.12238883
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
35.5	8	2.1%
38.1	7	1.8%
32.8	7	1.8%
35.7	7	1.8%
33.1	7	1.8%
33.4	6	1.6%
34.2	6	1.6%
34.5	5	1.3%
33.8	5	1.3%
35.3	5	1.3%
Other values (147)	317	83.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
22.9	1	0.3%
23.5	1	0.3%
23.9	1	0.3%
24.2	1	0.3%
26	1	0.3%
26.2	2	0.5%
26.3	1	0.3%
26.4	1	0.3%
26.9	2	0.5%
27.4	1	0.3%

Value	Count	Frequency (%)
70.5	1	0.3%
48.8	1	0.3%
47.9	1	0.3%
47.4	1	0.3%
47.3	1	0.3%
47	1	0.3%
46.9	1	0.3%
46.8	1	0.3%
45.9	1	0.3%
45.8	2	0.5%

Male Population
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	379
Distinct (%)	100.0%
Missing	1
Missing (%)	0.3%
Infinite	0
Infinite (%)	0.0%
Mean	98011.33245

Minimum	29995
Maximum	4081698
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	29995
5-th percentile	32282.9
Q1	38663
median	50405
Q3	79442
95-th percentile	267806.4
Maximum	4081698
Range	4051703
Interquartile range (IQR)	40779

Descriptive statistics

Standard deviation	241682.256
Coefficient of variation (CV)	2.465860324
Kurtosis	198.6629887
Mean	98011.33245
Median Absolute Deviation (MAD)	14434
Skewness	12.71059724
Sum	37146295
Variance	5.841031286 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
56229	1	0.3%
49186	1	0.3%
50680	1	0.3%
32211	1	0.3%
39221	1	0.3%
90192	1	0.3%
57961	1	0.3%
40015	1	0.3%
42100	1	0.3%
43314	1	0.3%
Other values (369)	369	97.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
29995	1	0.3%
30193	1	0.3%
30758	1	0.3%
30844	1	0.3%
30890	1	0.3%
31205	1	0.3%
31248	1	0.3%
31369	1	0.3%
31382	1	0.3%
31395	1	0.3%

Value	Count	Frequency (%)
4081698	1	0.3%
1320015	1	0.3%
1149686	1	0.3%
786833	1	0.3%
721405	1	0.3%
693826	1	0.3%
639019	1	0.3%
518317	1	0.3%
475718	1	0.3%
439752	1	0.3%

Female Population
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	378
Distinct (%)	99.7%
Missing	1
Missing (%)	0.3%
Infinite	0
Infinite (%)	0.0%
Mean	102475.8945

Minimum	27348
Maximum	4468707
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	27348
5-th percentile	33947.4
Q1	40886
median	51265
Q3	83314
95-th percentile	272885.1
Maximum	4468707
Range	4441359
Interquartile range (IQR)	42428

Descriptive statistics

Standard deviation	260279.9006
Coefficient of variation (CV)	2.53991343
Kurtosis	212.6129316
Mean	102475.8945
Median Absolute Deviation (MAD)	14172
Skewness	13.25191261
Sum	38838364
Variance	6.774562664 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
35801	2	0.5%
62432	1	0.3%
56128	1	0.3%
35234	1	0.3%
36911	1	0.3%
92175	1	0.3%
58784	1	0.3%
27348	1	0.3%
46407	1	0.3%
45456	1	0.3%
Other values (368)	368	96.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
27348	1	0.3%
31456	1	0.3%
32173	1	0.3%
32397	1	0.3%
32763	1	0.3%
32799	1	0.3%
32807	1	0.3%
32901	1	0.3%
33094	1	0.3%
33310	1	0.3%

Value	Count	Frequency (%)
4468707	1	0.3%
1400541	1	0.3%
1148942	1	0.3%
776168	1	0.3%
748419	1	0.3%
701081	1	0.3%
661063	1	0.3%
508602	1	0.3%
456122	1	0.3%
448828	1	0.3%

Total Population
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	380
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	200150.6553

Minimum	63651
Maximum	8550405
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	63651
5-th percentile	67358.4
Q1	79001.25
median	103332
Q3	161607.5
95-th percentile	536182.75
Maximum	8550405
Range	8486754
Interquartile range (IQR)	82606.25

Descriptive statistics

Standard deviation	501249.5923
Coefficient of variation (CV)	2.504361485
Kurtosis	206.4515152
Mean	200150.6553
Median Absolute Deviation (MAD)	28802
Skewness	13.00940053
Sum	76057249
Variance	2.512511537 × 10¹¹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
118661	1	0.3%
102467	1	0.3%
100884	1	0.3%
67445	1	0.3%
76132	1	0.3%
182367	1	0.3%
116745	1	0.3%
67363	1	0.3%
88507	1	0.3%
88770	1	0.3%
Other values (370)	370	97.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
63651	1	0.3%
63792	1	0.3%
64609	1	0.3%
64819	1	0.3%
64837	1	0.3%
64962	1	0.3%
65065	1	0.3%
65265	1	0.3%
65299	1	0.3%
65532	1	0.3%

Value	Count	Frequency (%)
8550405	1	0.3%
2720556	1	0.3%
2298628	1	0.3%
1563001	1	0.3%
1469824	1	0.3%
1394907	1	0.3%
1300082	1	0.3%
1026919	1	0.3%
931840	1	0.3%
868031	1	0.3%

Number of Veterans
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	375
Distinct (%)	98.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9073.757895

Minimum	416
Maximum	156961
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	416
5-th percentile	1669.75
Q1	3529.25
median	4980.5
Q3	8392.5
95-th percentile	29448.3
Maximum	156961
Range	156545
Interquartile range (IQR)	4863.25

Descriptive statistics

Standard deviation	14435.63488
Coefficient of variation (CV)	1.590921319
Kurtosis	40.78164889
Mean	9073.757895
Median Absolute Deviation (MAD)	2140
Skewness	5.544698286
Sum	3448028
Variance	208387554.3
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3404	2	0.5%
5204	2	0.5%
1376	2	0.5%
3027	2	0.5%
4211	2	0.5%
4973	1	0.3%
6888	1	0.3%
4957	1	0.3%
2126	1	0.3%
2855	1	0.3%
Other values (365)	365	96.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
416	1	0.3%
629	1	0.3%
693	1	0.3%
705	1	0.3%
724	1	0.3%
897	1	0.3%
1066	1	0.3%
1101	1	0.3%
1131	1	0.3%
1190	1	0.3%

Value	Count	Frequency (%)
156961	1	0.3%
109089	1	0.3%
92489	1	0.3%
75432	1	0.3%
72388	1	0.3%
72042	1	0.3%
71898	1	0.3%
54995	1	0.3%
49291	1	0.3%
47693	1	0.3%

Foreign-born
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	379
Distinct (%)	99.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	45226.97632

Minimum	1058
Maximum	3212500
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	1058
5-th percentile	4175.55
Q1	12056
median	21120.5
Q3	34742.5
95-th percentile	113255.7
Maximum	3212500
Range	3211442
Interquartile range (IQR)	22686.5

Descriptive statistics

Standard deviation	175284.3482
Coefficient of variation (CV)	3.875659229
Kurtosis	283.6036436
Mean	45226.97632
Median Absolute Deviation (MAD)	11092
Skewness	15.93392508
Sum	17186251
Variance	3.072460271 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5757	2	0.5%
12070	1	0.3%
28133	1	0.3%
29691	1	0.3%
40666	1	0.3%
59655	1	0.3%
3732	1	0.3%
6630	1	0.3%
14775	1	0.3%
9704	1	0.3%
Other values (369)	369	97.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1058	1	0.3%
1062	1	0.3%
1224	1	0.3%
1531	1	0.3%
1815	1	0.3%
1884	1	0.3%
2138	1	0.3%
2204	1	0.3%
2258	1	0.3%
2829	1	0.3%

Value	Count	Frequency (%)
3212500	1	0.3%
696210	1	0.3%
573463	1	0.3%
401493	1	0.3%
373842	1	0.3%
326825	1	0.3%
300702	1	0.3%
297199	1	0.3%
260789	1	0.3%
208046	1	0.3%

Average Household Size
Real number (ℝ_≥0)

Distinct	143
Distinct (%)	37.7%
Missing	1
Missing (%)	0.3%
Infinite	0
Infinite (%)	0.0%
Mean	2.806965699

Minimum	2
Maximum	4.98
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	3.1 KiB

Quantile statistics

Minimum	2
5-th percentile	2.24
Q1	2.48
median	2.7
Q3	3.04
95-th percentile	3.673
Maximum	4.98
Range	2.98
Interquartile range (IQR)	0.56

Descriptive statistics

Standard deviation	0.46817616
Coefficient of variation (CV)	0.1667908376
Kurtosis	2.31726247
Mean	2.806965699
Median Absolute Deviation (MAD)	0.27
Skewness	1.286587442
Sum	1063.84
Variance	0.2191889168
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2.72	9	2.4%
2.73	8	2.1%
2.85	8	2.1%
2.64	7	1.8%
3.13	6	1.6%
2.52	6	1.6%
2.78	6	1.6%
2.45	6	1.6%
2.97	6	1.6%
2.59	6	1.6%
Other values (133)	311	81.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2	1	0.3%
2.06	1	0.3%
2.08	2	0.5%
2.13	1	0.3%
2.17	2	0.5%
2.18	2	0.5%
2.19	1	0.3%
2.2	1	0.3%
2.21	1	0.3%
2.22	3	0.8%

Value	Count	Frequency (%)
4.98	1	0.3%
4.78	1	0.3%
4.58	1	0.3%
4.57	1	0.3%
4.15	1	0.3%
4.08	2	0.5%
3.97	1	0.3%
3.93	1	0.3%
3.9	1	0.3%
3.89	1	0.3%

State Code
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	17
Distinct (%)	4.5%
Missing	0
Missing (%)	0.0%
Memory size	3.1 KiB

CA	114
TX	48
FL	41
IL	19
MI	15
Other values (12)	143

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	760
Distinct characters	17
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	IL
2nd row	VA
3rd row	CO
4th row	AZ
5th row	TX

Common Values

Value	Count	Frequency (%)
CA	114	30.0%
TX	48	12.6%
FL	41	10.8%
IL	19	5.0%
MI	15	3.9%
CO	15	3.9%
AZ	14	3.7%
WA	14	3.7%
VA	13	3.4%
MA	13	3.4%
Other values (7)	74	19.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ca	114	30.0%
tx	48	12.6%
fl	41	10.8%
il	19	5.0%
mi	15	3.9%
co	15	3.9%
az	14	3.7%
wa	14	3.7%
ma	13	3.4%
va	13	3.4%
Other values (7)	74	19.5%

Most occurring characters

Value	Count	Frequency (%)
A	168	22.1%
C	141	18.6%
L	60	7.9%
N	54	7.1%
T	48	6.3%
X	48	6.3%
M	48	6.3%
I	44	5.8%
F	41	5.4%
O	25	3.3%
Other values (7)	83	10.9%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	760	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	168	22.1%
C	141	18.6%
L	60	7.9%
N	54	7.1%
T	48	6.3%
X	48	6.3%
M	48	6.3%
I	44	5.8%
F	41	5.4%
O	25	3.3%
Other values (7)	83	10.9%

Most occurring scripts

Value	Count	Frequency (%)
Latin	760	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	168	22.1%
C	141	18.6%
L	60	7.9%
N	54	7.1%
T	48	6.3%
X	48	6.3%
M	48	6.3%
I	44	5.8%
F	41	5.4%
O	25	3.3%
Other values (7)	83	10.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	760	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	168	22.1%
C	141	18.6%
L	60	7.9%
N	54	7.1%
T	48	6.3%
X	48	6.3%
M	48	6.3%
I	44	5.8%
F	41	5.4%
O	25	3.3%
Other values (7)	83	10.9%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Unnamed: 0	City	State	Median Age	Male Population	Female Population	Total Population	Number of Veterans	Foreign-born	Average Household Size	State Code
0	1	Peoria	Illinois	33.1	56229.0	62432.0	118661	6634.0	7517.0	2.40	IL
1	3	Hampton	Virginia	35.5	66214.0	70240.0	136454	19638.0	6204.0	2.48	VA
2	4	Lakewood	Colorado	37.7	76013.0	76576.0	152589	9988.0	14169.0	2.29	CO
3	5	Mesa	Arizona	36.9	234998.0	236835.0	471833	31808.0	57492.0	2.68	AZ
4	6	Bryan	Texas	29.4	41761.0	40345.0	82106	3602.0	12014.0	2.55	TX
5	7	Garland	Texas	34.5	116406.0	120430.0	236836	10407.0	62975.0	3.12	TX
6	8	Springfield	Illinois	38.8	55639.0	62170.0	117809	7525.0	4264.0	2.22	IL
7	9	Flint	Michigan	35.3	48984.0	49313.0	98297	3757.0	2138.0	2.38	MI
8	10	Tacoma	Washington	37.7	100914.0	107036.0	207950	19040.0	31863.0	2.48	WA
9	12	Eagan	Minnesota	36.8	31587.0	34701.0	66288	2699.0	8642.0	2.49	MN

Last rows

	Unnamed: 0	City	State	Median Age	Male Population	Female Population	Total Population	Number of Veterans	Foreign-born	Average Household Size	State Code
370	1581	Vancouver	Washington	37.2	82958.0	89895.0	172853	12391.0	21748.0	2.49	WA
371	1604	Minneapolis	Minnesota	32.4	206547.0	204388.0	410935	15217.0	70769.0	2.26	MN
372	1609	San Buenaventura	California	37.7	53932.0	55785.0	109717	5980.0	18025.0	2.68	CA
373	1645	Harlingen	Texas	30.1	32404.0	33365.0	65769	2761.0	10391.0	3.00	TX
374	1651	San Leandro	California	41.8	43032.0	47679.0	90711	4111.0	34293.0	2.79	CA
375	1657	Tyler	Texas	33.9	50422.0	53283.0	103705	4813.0	8225.0	2.59	TX
376	1762	Menifee	California	37.1	42866.0	44297.0	87163	6821.0	12481.0	3.06	CA
377	1774	Gainesville	Florida	26.0	60803.0	69330.0	130133	4788.0	15272.0	2.33	FL
378	1931	Bellflower	California	33.4	38936.0	39498.0	78434	2154.0	24607.0	3.58	CA
379	1963	Camden	New Jersey	27.9	36437.0	39694.0	76131	1425.0	11317.0	3.00	NJ

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Dash Punctuation

Other Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Interactions

Correlations

Spearman's ρ

Pearson's r

Kendall's τ

Cramér's V (φc)

Phik (φk)

Missing values

Sample

First rows

Last rows